In the past, networks, such as networks at Layers 0, 1, 2, and/or 3, only provided services to long-term static end-to-end connections. In networks, the services can be provisioned through Layer 0 (Wave Division Multiplexing (WDM)) and Layer 1 (Time Division Multiplexing (TDM)) connections. Networks are increasingly supporting on-demand services with dynamic connections. These on-demand connections will have varied durations and bandwidth requirements and may be scheduled in advance or may arrive spontaneously. Ongoing connection arrivals and releases lead to less than ideal resource utilization over time: a connection which used resources optimally when it was established may no longer be optimally routed as a result of capacity that is freed by subsequent connection releases. The resulting stranded bandwidth results in poorer network utilization, over time, and ultimately higher network cost.
Conventional network reconfiguration includes various reconfiguration triggers, periodicity, and grooming in both static and dynamic loads, and a survey of conventional techniques is described in Jing Wu, “A Survey of WDM network reconfiguration: Strategies and Triggering Methods”, Computer Networks 55 (2011) 2622-2645. Existing approaches to the bandwidth optimization also applied to quasi-static transport networks that changed state slowly as opposed to the rapidly evolving dynamic network. Historically linear or integer programming techniques were used as the basis of reconfiguration algorithms. Historically, reconfiguration did not consider scheduled connections or the associated optimizations moving connections in time as well as space.
Optical transport networks, for example, previously supported long-term static end-to-end connections. This is changing with the introduction of SDN and with its use for dynamic connections. Dynamic connections have both varied bandwidth requirements and durations. Connection requests and releases will occur with varying rates and often randomly both in location and in time. No mechanism currently exists within SDN to ensure that the utilization of network resources does not degrade as it responds to dynamically changing loads thereby reducing capacity and ultimately increasing the operators' costs. The highly variable and typically unpredictable arrival and release of dynamic connections will from-time-to-time exceed the capacity of the network. Simulation studies have shown that overloads can lead to a capacity collapse where connections are established with inefficient paths that waste resources.